Metadata-Version: 2.1
Name: tflite-support-nightly
Version: 0.4.4.dev20230625
Summary: TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile devices.
Home-page: https://www.tensorflow.org/
Download-URL: https://github.com/tensorflow/tflite-support/tags
Author: Google, LLC.
Author-email: packages@tensorflow.org
License: Apache 2.0
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: absl-py (>=0.7.0)
Requires-Dist: numpy (>=1.20.0)
Requires-Dist: flatbuffers (>=2.0)
Requires-Dist: protobuf (<4,>=3.18.0)
Requires-Dist: sounddevice (>=0.4.4)
Requires-Dist: pybind11 (>=2.6.0)

TFLite Support is a toolkit that helps users to develop ML and deploy TFLite models onto mobile devices.

This PyPI package includes the Python bindings for following features:

 - Task Library: a set of powerful and easy-to-use task-specific libraries to
 integrate TFLite models onto various platforms. See the [Task Library
 documentation](https://www.tensorflow.org/lite/inference_with_metadata/task_library/overview)
 for more information.
 - Metadata schemas: wraps TFLite model schema and metadata schema in Python.
 - Metadata writer and displayer: can be used to populate the metadata and
 associated files into the model, as well as converting the populated metadata
 into the json format. See the [Metadata
 documentation](https://www.tensorflow.org/lite/convert/metadata) for more
 information.
 - Android Codegen tool: generates the Java model interface used in Android for
 a particular model. See the [Codegen tool
 documentation](https://www.tensorflow.org/lite/inference_with_metadata/codegen)
 for more information.
